Hi Akil,
It didnt work. Here is the code...
package com.paypal;
import org.apache.spark.SparkConf;
import org.apache.spark.storage.StorageLevel;
import org.apache.spark.streaming.api.java.JavaPairInputDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;
import org.apache.spark.api.java.*;
import org.apache.spark.api.java.function.*;
import org.apache.spark.streaming.*;
import org.apache.spark.streaming.api.java.*;
import com.google.common.collect.Lists;
import org.apache.spark.streaming.receiver.Receiver;
import scala.Tuple2;
import java.net.ConnectException;
import java.net.Socket;
import java.util.Arrays;
import java.util.regex.Pattern;
import java.io.*;
/**
* Hello world!
*
*/
public class App3
{
private static final Pattern SPACE = Pattern.compile(" ");
public static void main(String[] args) {
// Create the context with a 1 second batch size
SparkConf sparkConf = new
SparkConf().setAppName("JavaNetworkWordCount");
// ******* always give local[4] to execute and see the output
JavaStreamingContext ssc = new JavaStreamingContext("local[4]",
"JavaNetworkWordCount", new Duration(5000));
// throws an error saying requires JavaPairDstream and not JavaDstream.
JavaDStream<String> lines =
ssc.fileStream("/Users/../Desktop/alarms.log");
JavaDStream<String> words = lines.flatMap(
new FlatMapFunction<String, String>() {
public Iterable<String> call(String s) {
return Arrays.asList(s.split(" "));
}
}
);
JavaPairDStream<String, Integer> ones = words.map(
new Function<String, Integer>() {
public Tuple2<String, Integer> call(String s) {
return new Tuple2(s, 1);
}
}
);
JavaPairDStream<String, Integer> counts = ones.reduceByKey(
new Function2<Integer, Integer, Integer>() {
public Integer call(Integer i1, Integer i2) {
return i1 + i2;
}
}
);
System.out.println("Hello world");
wordCounts.print();
ssc.start();
ssc.awaitTermination();
}
}
I am not able to figure out how to type cast the objects of Type
JavaPairDStream to JDstream. Can you provide me a working code for the same.
Thanks in advance.
Regards
Aravindan
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